Antimicrobial peptide DiPGLa-H exhibits the most outstanding anti-infective activity among the PGLa variants based on a systematic comparison
Bibliographic record
Abstract
ABSTRACT The escalating threat of antibiotic-resistant bacteria has heightened global interest in antimicrobial peptides as promising candidates due to their potent broad-spectrum activity and low likelihood of resistance development. Despite this potential, these peptides face challenges, including modest bactericidal efficacy, insufficient safety assessment, and expensive production. In this study, we systematically evaluated a panel of nine AMP variants of PGLa, a natural AMP derived from Xenopus laevis . All peptides retained α-helical structures and exhibited high biocompatibility, with hemolytic concentrations above 128 µg/mL and macrophage survival rates over 80%. Among them, a tandem-repeat variant DiPGLa-H demonstrated the most potent antimicrobial activity, with a therapeutic index of 35.94, against key pathogens such as Escherichia coli, Staphylococcus aureus, and Acinetobacter baumannii . A DAMP4-DiPGLa-H fusion protein was engineered to mitigate potential host toxicity, and we achieved high-purity biosynthesis of DiPGLa-H by employing a combination of acid cleavage and non-chromatographic purification, with yields reaching 21.2 mg/mL. The biosynthesized DiPGLa-H exhibited robust stability across a wide pH range and high temperatures, effectively disrupting biofilms formed by multiple pathogenic species. Mechanistically, DiPGLa-H disrupts both the inner and outer bacterial membranes, causing cell shrinkage, vesiculation, and intracellular leakage. In vivo , DiPGLa-H significantly improved survival rates in mice with induced peritoneal inflammation by 31%–38% while reducing bacterial burdens in key organs by 100-fold to 1,000-fold. These findings unearthed DiPGLa-H as a highly promising AMP. Moreover, the successful development of a cost-effective, high-purity biosynthesis method for DiPGLa-H, utilizing DAMP4 fusion technology, enables its low-cost application in combating multidrug-resistant pathogens. IMPORTANCE AMPs are innate defense molecules in animals, plants, and microorganisms. Notably, one-third of these peptides in databases originate from amphibians. We discovered that naturally weak AMPs from this source can be enhanced through artificial design. Specifically, variant DiPGLa-H showed superior germicidal efficacy and cell selectivity both in vivo and in vitro and can be biosynthesized and purified by combining DAMP4 fusion protein strategy and a simple non-chromatographic method that facilitates large-scale production. Our focus is on understanding the structure-activity relationships of PGLa. Furthermore, the development of a non-chromatographic purification technique for AMPs offers a viable pathway for the large-scale production of these essential compounds.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".